Most CEOs often dream of the moment they ring the Nasdaq opening bell, symbolizing their company's arrival on the public stage. Sam Altman, CEO of OpenAI, notably deviates from this common sentiment. During a December episode of the "Big Technology Podcast" hosted by Alex Kantrowitz, Altman articulated a candid assessment of the potential public listing of his company, characterizing his personal excitement about becoming a public company CEO as nonexistent—stating it as "0%." He further elaborated that in some respects, transitioning OpenAI into a public entity could prove "really annoying."
This frank viewpoint emerged amid discussions about whether OpenAI might pursue an initial public offering (IPO) anytime soon. When directly questioned about possibly taking the company public before external funding pressures necessitate it, Altman acknowledged several factors influencing the decision. He noted the appeal of public markets as a means for investors to partake in value creation but also reflected on the company’s relative lateness to such a step compared to other firms, saying, "...in some sense, we will be very late to go public if you look at any previous company."
Despite recognizing the allure of public capital, Altman defended the merits of remaining a private enterprise. He emphasized OpenAI’s significant capital needs and suggested the company will eventually exceed typical shareholder limits, implying continued private fund-raising efforts in the foreseeable future. This stance aligns with a growing Silicon Valley trend where companies delay IPOs, leveraging deep private capital pools as an alternative growth mechanism.
Platforms like Fundrise illustrate this evolving investment landscape by enabling individual investors to participate in funding private tech ventures—a model supporting long-term investments in companies that operate privately for many years during scaling phases, echoing Altman’s narrative.
The most impactful moment from the podcast came when Altman bluntly addressed his personal enthusiasm about leading a public company: "Am I excited to be a public company CEO? 0%. Am I excited for OpenAI to be a public company? In some ways, I am. And in some ways, I think it'll be really annoying." Although he did not detail the specific aspects he finds bothersome, one can reasonably infer this relates to the regulatory burden, mandatory earnings calls, intensive public shareholder scrutiny, and other typical public company obligations. To date, OpenAI has avoided these challenges by staying private.
Despite this public aversion, OpenAI operates on a scale characteristic of large corporations. Altman revealed that the company’s computational resources have approximately tripled over the last year and are projected to triple again in 2026. This substantial scaling is part of OpenAI’s strategy to meet rising demand for artificial intelligence models across both enterprise and consumer sectors.
OpenAI’s reputation for aggressive investment in model training infrastructure, including custom silicon, remains intact. When a projected long-term infrastructure capital requirement of $1.4 trillion was brought up during the interview, Altman neither disputed the figure nor downplayed it, remarking only that such an investment would span a lengthy period.
Altman observed that revenue growth matches or slightly exceeds the expansion of compute capacity. "Our revenue grows even a little bit faster than [compute], but it does roughly track our compute fleet," he explained. He further illustrated this by noting that if compute resources were doubled, revenue would approximately double in tandem.
Regarding profitability, Altman acknowledged that sustained growth in training costs delays reaching profitability milestones. He said, "If we weren't continuing to grow our training costs by so much, we would be profitable way, way earlier." This statement underscores an intentional trade-off in favor of extensive upfront investment in model training and infrastructure, with monetization expected to follow subsequently.
Kantrowitz also raised the topic of the company incurring debt, a matter that has attracted scrutiny from financial analysts. Altman downplayed concerns about debt usage, suggesting that employing capital markets to finance AI infrastructure development is a logical approach. He also hinted at the emergence of innovative financial instruments beyond traditional equity and debt, saying, "There will also be other kinds of financial instruments," and appeared amenable to the notion of lenders providing capital to build AI data centers.
While Altman clearly does not relish the prospect of regularly reporting to Wall Street and enduring its summons every quarter, he acknowledges that such a reality likely awaits OpenAI eventually. The progression toward public markets may be unavoidable, whether he finds it appealing or not.
OpenAI is currently advancing toward artificial general intelligence (AGI)-level models, continuously redefining the bounds of superintelligence, and developing proprietary AI-native hardware designed without traditional screens. These ambitious initiatives indicate that sustaining prolonged operation as a private entity could become impractical in the long term. Ultimately, despite reservations, the inevitability of an IPO looms.
Should Altman find himself standing on a stock exchange balcony to celebrate an OpenAI public debut someday, it would be uncharacteristic to expect an exuberant expression. His remarks convey a leader more focused on pragmatic constraints and the demanding reality of public company governance than on celebratory fanfare.